TrackFit
Progress your fitness goals using machine learning
TrackFit launched on September 16, 2025 with 94 votes, #330 of 8,160 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
The Personal Fitness Tracker! This Streamlit-based web application allows users to predict the calories burned during exercise. The app leverages machine learning models to provide accurate predictions and helps users track their fitness journey over time.
Welcome to the Personal Fitness Tracker! This Streamlit-based web application allows users to predict the calories burned during exercise based on their personal details. The app leverages machine learning models to provide accurate predictions and helps users track their fitness journey over time. - KimmiKumari07/TrackFit
Welcome to the Personal Fitness Tracker ! This Streamlit-based web application allows users to predict the calories burned during exercise based on their personal details. The app leverages machine learning models to provide accurate predictions and helps users track their fitness journey over time. pip install -r requirements.txt 2️⃣ Ensure Model Files Are in Place Make sure you have the pre-trained model files in the models/ directory: models/ ├── svm_model.pkl ├── logistic_regression_model.pkl └── random_forest_model.pkl If these files are missing, retrain and save models using joblib before running the app. streamlit run app.py 🛠 Technologies Used Python Streamlit (for UI and…from github.com
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